The present invention relates to an image matching method.
Two methods are known in the art of image analysis. One is the motion coherence method using "interest" operators and is described in an article "The Motion Coherence Theory" by Alan L. Yuille and Norberto M. Grzywacz, International Conference on Computer Vision, I.E.E.E., pages 344-353, 1988. The other is the block matching method which is described in Japanese Patent 62-107386 "Image Matching Method" and in U.S. Pat. No. 4,677,476 issued to T. Kondo, "Method for Detecting a Movement of a Television Signal." With the former technique, characteristic features of an image are detected using an "interest" operator and coincidence is detected between them. However, the features that can be extracted from a given image are limited in number and hence it is insufficient for detailed image analysis. In addition, available features are further limited to those having the same degree of reliability in all directions. For example, even if a brightness gradient exists in some point of an image, the features of this point cannot be extracted if that gradient exists only in one direction. To estimate possible correspondences between image points from which characteristic features cannot be extracted, a smoothing technique has been proposed to increase the number of available correspondences. However, the degree of precision attained with this approach is not satisfactory for high density matching.
With the block matching technique, a first image is segmented into a plurality of blocks and correlations between the first image and a second one are detected while moving each of the blocks in the same direction with respect to the second. When a maximum correlation value is detected, the block corresponding to that maximum correlation is identified as one corresponding to a portion of the second image. Although the number of possible correspondences available for high density matching may be satisfactory with the block matching method, one disadvantage is that a large number of errors occur when detecting matches between corresponding features. More specifically, if the brightness variations of a block are scarce, difficulty arises to detect a match, and if the brightness gradients of a given block exist only in one direction, a match may be detected with more than one corresponding block in the other image if the latter has a brightness gradient of the same direction as that of the given block, failing to uniquely detect a match. In addition, the parallel movement of a segmented block fails to detect a perfect match at a true point of correspondences if the images being compared contain features having a rotational relationship with each other.